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Artificial intelligence (opens in new tab) continues to make headlines for its potential to transform businesses across various industries, and has been widely embraced as a technology that can help companies unlock new opportunities, improve efficiency, and increase profitability. At its most basic level, AI does this by analyzing inputted information to create intelligent outputs. The AI industry is currently valued at over $136 billion and is predicted to grow over 13 times in the next 7 years.

At its core, AI relies on data (opens in new tab) - specifically, large volumes of high-quality data to train machine learning algorithms. These algorithms analyze inputted information to identify patterns that can be used to make predictions, automate processes, or perform other tasks. Accordingly, while the power of AI applications (opens in new tab) across industries is immense, the benefits are entirely based on the information available to these systems.

Given that AI is so reliant on data, where this data is stored becomes an important concern. Businesses need to know that they can securely store a large volume of data and that this data is easily accessible for the AI systems to use. Moreover, for businesses, proprietary data for custom AI applications must be kept safe. With this in mind, the best way for businesses to keep large quantities of easily accessible data safely is by keeping at least one copy of it in the cloud.

AI systems need high volumes of data on hand to operate optimally. These systems have the capacity to improve their performance and enhance their learning speed as the amount of available data increases. For example, Google DeepMind's AlphaGo Zero had to play 20 million games against itself to train its AI to a superhuman level of play, demonstrating just how much data is needed for AI to work at its full potential.

Given that the success of AI implementation hinges on the amount of data AI systems can access, companies must thoughtfully consider their data storage options, whether that be on-premise, in the cloud (opens in new tab), or in a hybrid cloud system - and how that impacts their AI implementation.

Storing data on local hardware owned and managed by an enterprise, known as on-premises data storage, requires securing storage resources and maintaining systems. However, scaling in this way is difficult and costly compared to cloud-based storage, which is better equipped to handle increasing data volumes. On-premise scalability is also limited by ageing hardware and software, which often come with discontinued support plans and retired products. Therefore, for better scalability and security, the adoption of cloud storage services is becoming increasingly crucial for companies as they develop "AI first" strategies.

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David Friend is the co-founder and CEO of Wasabi.

Similar to the way businesses need to store a lot of data for AI, they also need to keep proprietary data should they wish to customize their AI to meet their organization's specific needs. For instance, an HR manager may be able to use AI to analyze years worth of company-wide survey data in minutes and predict employee responses to different kinds of company news, like new policies or team switchups. Similarly, an AI system could analyze company growth and economic data to inform major business decisions.

Incorporating proprietary data into an AI system improves the accuracy and relevance of insights leading to better decision-making and business outcomes. Customising AI applications using proprietary data can give businesses a competitive edge, however should they choose to take advantage of customised AI through proprietary data, its important that this data is stored safely.

Unfortunately, the rise of AI systems brings with it a host of new cybersecurity risks and the number and cost of cybersecurity attacks is expected to surge in the next five years, rising from $8.44 trillion in 2022 to $23.84 trillion by 2027. Particularly when storing critical company data, its key that AI systems are well-protected against ransomware attacks.

An important security advantage cloud has over on-premise solutions is that cloud infrastructure is separated from user workstations, bearing in mind hackers most commonly access company networks through phishing and emails (opens in new tab). Accordingly, having multiple copies of data with at least one version stored in the cloud is key to keeping company data safe and not compromising any critical AI systems.

The best way to protect against threats that may compromise the primary data copy is to keep a second, immutable copy of the AI system data. Immutable storage is a cloud storage feature that provides extra security by preventing data modification or deletion. Combined with comprehensive backup strategies, cloud storage (opens in new tab) providers offer high data security by storing immutable backups that can be retrieved if original data is compromised or deleted, ensuring availability, and avoiding loss of critical data.

For businesses, the value of AI is in its convenience and potential cost savings as it takes on tasks that would have previously taken hours of employee time and energy. By embracing cloud storage solutions for the reasons set out above, businesses can unleash the full power of AI for success.

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Cloud storage is the key to unlocking AI's full potential for businesses - TechRadar